Human motion tracking approach for stroke rehabilitation
Real-time tracking of human body motion is an important technology in synthetic environments, robotics, and other human–computer interaction applications [25]. In this project, the author test and experimented the various type of human upper and lower limbs motion tracking with Inertia Measurement U...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2011
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/45372 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-45372 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-453722023-07-07T16:06:03Z Human motion tracking approach for stroke rehabilitation Chua, Evelyn Sock Puay. Xie Lihua School of Electrical and Electronic Engineering Singapore Polytechnic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Real-time tracking of human body motion is an important technology in synthetic environments, robotics, and other human–computer interaction applications [25]. In this project, the author test and experimented the various type of human upper and lower limbs motion tracking with Inertia Measurement Unit. The author works at Singapore Polytechnic for this project. This paper presents the used of inertial measurement unit (IMU) named InterSense Wireless InertialCube3 for the real-time estimation of human limb segments. The IMU used in first part of this paper concentrates on capturing human upper limb motion, namely the wrist rotational angle and elbow joint angle. The quaternion-based Extended Kalman Filter (EKF) was implemented for the sensor fusion of the hybrid system to retrieve the performance of the human lower limb. The hybrid system uses at the second part includes IMU calculated position reading and OpticTrack position data. The both parts of this paper are essential in helping the stroke rehabilitation in a modernize manner. Bachelor of Engineering 2011-06-13T03:38:15Z 2011-06-13T03:38:15Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/45372 en Nanyang Technological University 91 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics |
spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Chua, Evelyn Sock Puay. Human motion tracking approach for stroke rehabilitation |
description |
Real-time tracking of human body motion is an important technology in synthetic environments, robotics, and other human–computer interaction applications [25]. In this project, the author test and experimented the various type of human upper and lower limbs motion tracking with Inertia Measurement Unit.
The author works at Singapore Polytechnic for this project. This paper presents the used of inertial measurement unit (IMU) named InterSense Wireless InertialCube3 for the real-time estimation of human limb segments.
The IMU used in first part of this paper concentrates on capturing human upper limb motion, namely the wrist rotational angle and elbow joint angle.
The quaternion-based Extended Kalman Filter (EKF) was implemented for the sensor fusion of the hybrid system to retrieve the performance of the human lower limb. The hybrid system uses at the second part includes IMU calculated position reading and OpticTrack position data.
The both parts of this paper are essential in helping the stroke rehabilitation in a modernize manner. |
author2 |
Xie Lihua |
author_facet |
Xie Lihua Chua, Evelyn Sock Puay. |
format |
Final Year Project |
author |
Chua, Evelyn Sock Puay. |
author_sort |
Chua, Evelyn Sock Puay. |
title |
Human motion tracking approach for stroke rehabilitation |
title_short |
Human motion tracking approach for stroke rehabilitation |
title_full |
Human motion tracking approach for stroke rehabilitation |
title_fullStr |
Human motion tracking approach for stroke rehabilitation |
title_full_unstemmed |
Human motion tracking approach for stroke rehabilitation |
title_sort |
human motion tracking approach for stroke rehabilitation |
publishDate |
2011 |
url |
http://hdl.handle.net/10356/45372 |
_version_ |
1772828067026173952 |